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<meta charset="utf-8" /><meta http-equiv="content-security-policy" content=""><meta name="hf:doc:metadata" content="{&quot;local&quot;:&quot;cloud-storage&quot;,&quot;sections&quot;:[{&quot;local&quot;:&quot;set-up-your-cloud-storage-filesystem&quot;,&quot;sections&quot;:[{&quot;local&quot;:&quot;amazon-s3&quot;,&quot;title&quot;:&quot;Amazon S3&quot;},{&quot;local&quot;:&quot;google-cloud-storage&quot;,&quot;title&quot;:&quot;Google Cloud Storage&quot;},{&quot;local&quot;:&quot;azure-blob-storage&quot;,&quot;title&quot;:&quot;Azure Blob Storage&quot;}],&quot;title&quot;:&quot;Set up your cloud storage FileSystem&quot;},{&quot;local&quot;:&quot;load-and-save-your-datasets-using-your-cloud-storage-filesystem&quot;,&quot;sections&quot;:[{&quot;local&quot;:&quot;download-and-prepare-a-dataset-into-a-cloud-storage&quot;,&quot;sections&quot;:[{&quot;local&quot;:&quot;dask&quot;,&quot;title&quot;:&quot;Dask&quot;}],&quot;title&quot;:&quot;Download and prepare a dataset into a cloud storage&quot;}],&quot;title&quot;:&quot;Load and Save your datasets using your cloud storage FileSystem&quot;},{&quot;local&quot;:&quot;saving-serialized-datasets&quot;,&quot;title&quot;:&quot;Saving serialized datasets&quot;},{&quot;local&quot;:&quot;listing-serialized-datasets&quot;,&quot;sections&quot;:[{&quot;local&quot;:&quot;load-serialized-datasets&quot;,&quot;title&quot;:&quot;Load serialized datasets&quot;}],&quot;title&quot;:&quot;Listing serialized datasets&quot;}],&quot;title&quot;:&quot;Cloud storage&quot;}" data-svelte="svelte-1phssyn">
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<h1 class="relative group"><a id="cloud-storage" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#cloud-storage"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
<span>Cloud storage
</span></h1>
<p>🤗 Datasets supports access to cloud storage providers through a <code>fsspec</code> FileSystem implementations.
You can save and load datasets from any cloud storage in a Pythonic way.
Take a look at the following table for some example of supported cloud storage providers:</p>
<table><thead><tr><th>Storage provider</th>
<th>Filesystem implementation</th></tr></thead>
<tbody><tr><td>Amazon S3</td>
<td><a href="https://s3fs.readthedocs.io/en/latest/" rel="nofollow">s3fs</a></td></tr>
<tr><td>Google Cloud Storage</td>
<td><a href="https://gcsfs.readthedocs.io/en/latest/" rel="nofollow">gcsfs</a></td></tr>
<tr><td>Azure Blob/DataLake</td>
<td><a href="https://github.com/fsspec/adlfs" rel="nofollow">adlfs</a></td></tr>
<tr><td>Dropbox</td>
<td><a href="https://github.com/MarineChap/dropboxdrivefs" rel="nofollow">dropboxdrivefs</a></td></tr>
<tr><td>Google Drive</td>
<td><a href="https://github.com/intake/gdrivefs" rel="nofollow">gdrivefs</a></td></tr></tbody></table>
<p>This guide will show you how to save and load datasets with any cloud storage.
Here are examples for S3, Google Cloud Storage and Azure Blob Storage.</p>
<h2 class="relative group"><a id="set-up-your-cloud-storage-filesystem" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#set-up-your-cloud-storage-filesystem"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
<span>Set up your cloud storage FileSystem
</span></h2>
<h3 class="relative group"><a id="amazon-s3" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#amazon-s3"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
<span>Amazon S3
</span></h3>
<ol><li>Install the S3 dependency with 🤗 Datasets:</li></ol>
<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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<pre><!-- HTML_TAG_START -->&gt;&gt;&gt; pip <span class="hljs-keyword">install </span>datasets[<span class="hljs-built_in">s3</span>]<!-- HTML_TAG_END --></pre></div>
<ol start="2"><li>Define your credentials</li></ol>
<p>To use an anonymous connection, use <code>anon=True</code>.
Otherwise, include your <code>aws_access_key_id</code> and <code>aws_secret_access_key</code> whenever you are interacting with a private S3 bucket.</p>
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<pre><!-- HTML_TAG_START --><span class="hljs-meta">&gt;&gt;&gt; </span>storage_options = {<span class="hljs-string">&quot;anon&quot;</span>: <span class="hljs-literal">True</span>} <span class="hljs-comment"># for anonymous connection</span>
<span class="hljs-comment"># or use your credentials</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>storage_options = {<span class="hljs-string">&quot;key&quot;</span>: aws_access_key_id, <span class="hljs-string">&quot;secret&quot;</span>: aws_secret_access_key} <span class="hljs-comment"># for private buckets</span>
<span class="hljs-comment"># or use a botocore session</span>
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">import</span> botocore
<span class="hljs-meta">&gt;&gt;&gt; </span>s3_session = botocore.session.Session(profile=<span class="hljs-string">&quot;my_profile_name&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>storage_options = {<span class="hljs-string">&quot;session&quot;</span>: s3_session}<!-- HTML_TAG_END --></pre></div>
<ol start="3"><li>Create your FileSystem instance</li></ol>
<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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<pre><!-- HTML_TAG_START --><span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">import</span> s3fs
<span class="hljs-meta">&gt;&gt;&gt; </span>fs = s3fs.S3FileSystem(**storage_options)<!-- HTML_TAG_END --></pre></div>
<h3 class="relative group"><a id="google-cloud-storage" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#google-cloud-storage"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
<span>Google Cloud Storage
</span></h3>
<ol><li>Install the Google Cloud Storage implementation:</li></ol>
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<pre><!-- HTML_TAG_START --><span class="hljs-meta">&gt;&gt;&gt;</span> <span class="language-python">conda install -c conda-forge gcsfs</span>
# or install with pip
<span class="hljs-meta">&gt;&gt;&gt;</span> <span class="language-python">pip install gcsfs</span><!-- HTML_TAG_END --></pre></div>
<ol start="2"><li>Define your credentials</li></ol>
<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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<pre><!-- HTML_TAG_START --><span class="hljs-meta">&gt;&gt;&gt; </span>storage_options={<span class="hljs-string">&quot;token&quot;</span>: <span class="hljs-string">&quot;anon&quot;</span>} <span class="hljs-comment"># for anonymous connection</span>
<span class="hljs-comment"># or use your credentials of your default gcloud credentials or from the google metadata service</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>storage_options={<span class="hljs-string">&quot;project&quot;</span>: <span class="hljs-string">&quot;my-google-project&quot;</span>}
<span class="hljs-comment"># or use your credentials from elsewhere, see the documentation at https://gcsfs.readthedocs.io/</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>storage_options={<span class="hljs-string">&quot;project&quot;</span>: <span class="hljs-string">&quot;my-google-project&quot;</span>, <span class="hljs-string">&quot;token&quot;</span>: TOKEN}<!-- HTML_TAG_END --></pre></div>
<ol start="3"><li>Create your FileSystem instance</li></ol>
<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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<pre><!-- HTML_TAG_START --><span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">import</span> gcsfs
<span class="hljs-meta">&gt;&gt;&gt; </span>fs = gcsfs.GCSFileSystem(**storage_options)<!-- HTML_TAG_END --></pre></div>
<h3 class="relative group"><a id="azure-blob-storage" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#azure-blob-storage"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
<span>Azure Blob Storage
</span></h3>
<ol><li>Install the Azure Blob Storage implementation:</li></ol>
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<pre><!-- HTML_TAG_START --><span class="hljs-meta">&gt;&gt;&gt;</span> <span class="language-python">conda install -c conda-forge adlfs</span>
# or install with pip
<span class="hljs-meta">&gt;&gt;&gt;</span> <span class="language-python">pip install adlfs</span><!-- HTML_TAG_END --></pre></div>
<ol start="2"><li>Define your credentials</li></ol>
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<pre><!-- HTML_TAG_START --><span class="hljs-meta">&gt;&gt;&gt; </span>storage_options = {<span class="hljs-string">&quot;anon&quot;</span>: <span class="hljs-literal">True</span>} <span class="hljs-comment"># for anonymous connection</span>
<span class="hljs-comment"># or use your credentials</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>storage_options = {<span class="hljs-string">&quot;account_name&quot;</span>: ACCOUNT_NAME, <span class="hljs-string">&quot;account_key&quot;</span>: ACCOUNT_KEY) <span class="hljs-comment"># gen 2 filesystem</span>
<span class="hljs-comment"># or use your credentials with the gen 1 filesystem</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>storage_options={<span class="hljs-string">&quot;tenant_id&quot;</span>: TENANT_ID, <span class="hljs-string">&quot;client_id&quot;</span>: CLIENT_ID, <span class="hljs-string">&quot;client_secret&quot;</span>: CLIENT_SECRET}<!-- HTML_TAG_END --></pre></div>
<ol start="3"><li>Create your FileSystem instance</li></ol>
<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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<pre><!-- HTML_TAG_START --><span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">import</span> adlfs
<span class="hljs-meta">&gt;&gt;&gt; </span>fs = adlfs.AzureBlobFileSystem(**storage_options)<!-- HTML_TAG_END --></pre></div>
<h2 class="relative group"><a id="load-and-save-your-datasets-using-your-cloud-storage-filesystem" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#load-and-save-your-datasets-using-your-cloud-storage-filesystem"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
<span>Load and Save your datasets using your cloud storage FileSystem
</span></h2>
<h3 class="relative group"><a id="download-and-prepare-a-dataset-into-a-cloud-storage" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#download-and-prepare-a-dataset-into-a-cloud-storage"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
<span>Download and prepare a dataset into a cloud storage
</span></h3>
<p>You can download and prepare a dataset into your cloud storage by specifying a remote <code>output_dir</code> in <code>download_and_prepare</code>.
Don’t forget to use the previously defined <code>storage_options</code> containing your credentials to write into a private cloud storage.</p>
<p>The <code>download_and_prepare</code> method works in two steps:</p>
<ol><li>it first downloads the raw data files (if any) in your local cache. You can set your cache directory by passing <code>cache_dir</code> to <a href="/docs/datasets/v2.6.2/en/package_reference/loading_methods#datasets.load_dataset_builder">load_dataset_builder()</a></li>
<li>then it generates the dataset in Arrow or Parquet format in your cloud storage by iterating over the raw data files.</li></ol>
<p>Load a dataset builder from the Hugging Face Hub (see <a href="./loading#hugging-face-hub">how to load from the Hugging Face Hub</a>):</p>
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<pre><!-- HTML_TAG_START --><span class="hljs-meta">&gt;&gt;&gt; </span>output_dir = <span class="hljs-string">&quot;s3://my-bucket/imdb&quot;</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>builder = load_dataset_builder(<span class="hljs-string">&quot;imdb&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>builder.download_and_prepare(output_dir, storage_options=storage_options, file_format=<span class="hljs-string">&quot;parquet&quot;</span>)<!-- HTML_TAG_END --></pre></div>
<p>Load a dataset builder using a loading script (see <a href="./loading#local-loading-script">how to load a local loading script</a>):</p>
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<pre><!-- HTML_TAG_START --><span class="hljs-meta">&gt;&gt;&gt; </span>output_dir = <span class="hljs-string">&quot;s3://my-bucket/imdb&quot;</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>builder = load_dataset_builder(<span class="hljs-string">&quot;path/to/local/loading_script/loading_script.py&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>builder.download_and_prepare(output_dir, storage_options=storage_options, file_format=<span class="hljs-string">&quot;parquet&quot;</span>)<!-- HTML_TAG_END --></pre></div>
<p>Use your own data files (see <a href="./loading#local-and-remote-files">how to load local and remote files</a>):</p>
<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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<pre><!-- HTML_TAG_START --><span class="hljs-meta">&gt;&gt;&gt; </span>data_files = {<span class="hljs-string">&quot;train&quot;</span>: [<span class="hljs-string">&quot;path/to/train.csv&quot;</span>]}
<span class="hljs-meta">&gt;&gt;&gt; </span>output_dir = <span class="hljs-string">&quot;s3://my-bucket/imdb&quot;</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>builder = load_dataset_builder(<span class="hljs-string">&quot;csv&quot;</span>, data_files=data_files)
<span class="hljs-meta">&gt;&gt;&gt; </span>builder.download_and_prepare(output_dir, storage_options=storage_options, file_format=<span class="hljs-string">&quot;parquet&quot;</span>)<!-- HTML_TAG_END --></pre></div>
<p>It is highly recommended to save the files as compressed Parquet files to optimize I/O by specifying <code>file_format=&quot;parquet&quot;</code>.
Otherwise the dataset is saved as an uncompressed Arrow file.</p>
<p>You can also specify the size of the Parquet shard using <code>max_shard_size</code> (default is 500MB):</p>
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<pre><!-- HTML_TAG_START --><span class="hljs-meta">&gt;&gt;&gt; </span>builder.download_and_prepare(output_dir, storage_options=storage_options, file_format=<span class="hljs-string">&quot;parquet&quot;</span>, max_shard_size=<span class="hljs-string">&quot;1GB&quot;</span>)<!-- HTML_TAG_END --></pre></div>
<h4 class="relative group"><a id="dask" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#dask"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
<span>Dask
</span></h4>
<p>Dask is a parallel computing library and it has a pandas-like API for working with larger than memory Parquet datasets in parallel.
Dask can use multiple threads or processes on a single machine, or a cluster of machines to process data in parallel.
Dask supports local data but also data from a cloud storage.</p>
<p>Therefore you can load a dataset saved as sharded Parquet files in Dask with</p>
<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
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<pre><!-- HTML_TAG_START --><span class="hljs-keyword">import</span> dask.dataframe <span class="hljs-keyword">as</span> dd
df = dd.read_parquet(output_dir, storage_options=storage_options)
<span class="hljs-comment"># or if your dataset is split into train/valid/test</span>
df_train = dd.read_parquet(output_dir + <span class="hljs-string">f&quot;/<span class="hljs-subst">{builder.name}</span>-train-*.parquet&quot;</span>, storage_options=storage_options)
df_valid = dd.read_parquet(output_dir + <span class="hljs-string">f&quot;/<span class="hljs-subst">{builder.name}</span>-validation-*.parquet&quot;</span>, storage_options=storage_options)
df_test = dd.read_parquet(output_dir + <span class="hljs-string">f&quot;/<span class="hljs-subst">{builder.name}</span>-test-*.parquet&quot;</span>, storage_options=storage_options)<!-- HTML_TAG_END --></pre></div>
<p>You can find more about dask dataframes in their <a href="https://docs.dask.org/en/stable/dataframe.html" rel="nofollow">documentation</a>.</p>
<h2 class="relative group"><a id="saving-serialized-datasets" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#saving-serialized-datasets"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
<span>Saving serialized datasets
</span></h2>
<p>After you have processed your dataset, you can save it to your cloud storage with <a href="/docs/datasets/v2.6.2/en/package_reference/main_classes#datasets.Dataset.save_to_disk">Dataset.save_to_disk()</a>:</p>
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<pre><!-- HTML_TAG_START --><span class="hljs-comment"># saves encoded_dataset to amazon s3</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>encoded_dataset.save_to_disk(<span class="hljs-string">&quot;s3://my-private-datasets/imdb/train&quot;</span>, fs=fs)
<span class="hljs-comment"># saves encoded_dataset to google cloud storage</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>encoded_dataset.save_to_disk(<span class="hljs-string">&quot;gcs://my-private-datasets/imdb/train&quot;</span>, fs=fs)
<span class="hljs-comment"># saves encoded_dataset to microsoft azure blob/datalake</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>encoded_dataset.save_to_disk(<span class="hljs-string">&quot;adl://my-private-datasets/imdb/train&quot;</span>, fs=fs)<!-- HTML_TAG_END --></pre></div>
<div class="course-tip bg-gradient-to-br dark:bg-gradient-to-r before:border-green-500 dark:before:border-green-800 from-green-50 dark:from-gray-900 to-white dark:to-gray-950 border border-green-50 text-green-700 dark:text-gray-400"><p>Remember to define your credentials in your <a href="#set-up-your-cloud-storage-filesystem">FileSystem instance</a> <code>fs</code> whenever you are interacting with a private cloud storage.</p></div>
<h2 class="relative group"><a id="listing-serialized-datasets" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#listing-serialized-datasets"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
<span>Listing serialized datasets
</span></h2>
<p>List files from a cloud storage with your FileSystem instance <code>fs</code>, using <code>fs.ls</code>:</p>
<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
<div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div>
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<pre><!-- HTML_TAG_START --><span class="hljs-meta">&gt;&gt;&gt; </span>fs.ls(<span class="hljs-string">&quot;my-private-datasets/imdb/train&quot;</span>)
[<span class="hljs-string">&quot;dataset_info.json.json&quot;</span>,<span class="hljs-string">&quot;dataset.arrow&quot;</span>,<span class="hljs-string">&quot;state.json&quot;</span>]<!-- HTML_TAG_END --></pre></div>
<h3 class="relative group"><a id="load-serialized-datasets" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#load-serialized-datasets"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a>
<span>Load serialized datasets
</span></h3>
<p>When you are ready to use your dataset again, reload it with <a href="/docs/datasets/v2.6.2/en/package_reference/main_classes#datasets.Dataset.load_from_disk">Dataset.load_from_disk()</a>:</p>
<div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg>
<div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div>
Copied</div></button></div>
<pre><!-- HTML_TAG_START --><span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> datasets <span class="hljs-keyword">import</span> load_from_disk
<span class="hljs-comment"># load encoded_dataset from cloud storage</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>dataset = load_from_disk(<span class="hljs-string">&quot;s3://a-public-datasets/imdb/train&quot;</span>, fs=fs)
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-built_in">print</span>(<span class="hljs-built_in">len</span>(dataset))
<span class="hljs-number">25000</span><!-- HTML_TAG_END --></pre></div>
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